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<FONT color="green">001</FONT>    /*<a name="line.1"></a>
<FONT color="green">002</FONT>     * Licensed to the Apache Software Foundation (ASF) under one or more<a name="line.2"></a>
<FONT color="green">003</FONT>     * contributor license agreements.  See the NOTICE file distributed with<a name="line.3"></a>
<FONT color="green">004</FONT>     * this work for additional information regarding copyright ownership.<a name="line.4"></a>
<FONT color="green">005</FONT>     * The ASF licenses this file to You under the Apache License, Version 2.0<a name="line.5"></a>
<FONT color="green">006</FONT>     * (the "License"); you may not use this file except in compliance with<a name="line.6"></a>
<FONT color="green">007</FONT>     * the License.  You may obtain a copy of the License at<a name="line.7"></a>
<FONT color="green">008</FONT>     *<a name="line.8"></a>
<FONT color="green">009</FONT>     *      http://www.apache.org/licenses/LICENSE-2.0<a name="line.9"></a>
<FONT color="green">010</FONT>     *<a name="line.10"></a>
<FONT color="green">011</FONT>     * Unless required by applicable law or agreed to in writing, software<a name="line.11"></a>
<FONT color="green">012</FONT>     * distributed under the License is distributed on an "AS IS" BASIS,<a name="line.12"></a>
<FONT color="green">013</FONT>     * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.<a name="line.13"></a>
<FONT color="green">014</FONT>     * See the License for the specific language governing permissions and<a name="line.14"></a>
<FONT color="green">015</FONT>     * limitations under the License.<a name="line.15"></a>
<FONT color="green">016</FONT>     */<a name="line.16"></a>
<FONT color="green">017</FONT>    package org.apache.commons.math3.distribution;<a name="line.17"></a>
<FONT color="green">018</FONT>    <a name="line.18"></a>
<FONT color="green">019</FONT>    import java.io.Serializable;<a name="line.19"></a>
<FONT color="green">020</FONT>    <a name="line.20"></a>
<FONT color="green">021</FONT>    import org.apache.commons.math3.analysis.UnivariateFunction;<a name="line.21"></a>
<FONT color="green">022</FONT>    import org.apache.commons.math3.analysis.solvers.UnivariateSolverUtils;<a name="line.22"></a>
<FONT color="green">023</FONT>    import org.apache.commons.math3.exception.NotStrictlyPositiveException;<a name="line.23"></a>
<FONT color="green">024</FONT>    import org.apache.commons.math3.exception.NumberIsTooLargeException;<a name="line.24"></a>
<FONT color="green">025</FONT>    import org.apache.commons.math3.exception.OutOfRangeException;<a name="line.25"></a>
<FONT color="green">026</FONT>    import org.apache.commons.math3.exception.util.LocalizedFormats;<a name="line.26"></a>
<FONT color="green">027</FONT>    import org.apache.commons.math3.random.RandomGenerator;<a name="line.27"></a>
<FONT color="green">028</FONT>    import org.apache.commons.math3.random.RandomDataImpl;<a name="line.28"></a>
<FONT color="green">029</FONT>    import org.apache.commons.math3.util.FastMath;<a name="line.29"></a>
<FONT color="green">030</FONT>    <a name="line.30"></a>
<FONT color="green">031</FONT>    /**<a name="line.31"></a>
<FONT color="green">032</FONT>     * Base class for probability distributions on the reals.<a name="line.32"></a>
<FONT color="green">033</FONT>     * Default implementations are provided for some of the methods<a name="line.33"></a>
<FONT color="green">034</FONT>     * that do not vary from distribution to distribution.<a name="line.34"></a>
<FONT color="green">035</FONT>     *<a name="line.35"></a>
<FONT color="green">036</FONT>     * @version $Id: AbstractRealDistribution.java 1422195 2012-12-15 06:45:18Z psteitz $<a name="line.36"></a>
<FONT color="green">037</FONT>     * @since 3.0<a name="line.37"></a>
<FONT color="green">038</FONT>     */<a name="line.38"></a>
<FONT color="green">039</FONT>    public abstract class AbstractRealDistribution<a name="line.39"></a>
<FONT color="green">040</FONT>    implements RealDistribution, Serializable {<a name="line.40"></a>
<FONT color="green">041</FONT>        /** Default accuracy. */<a name="line.41"></a>
<FONT color="green">042</FONT>        public static final double SOLVER_DEFAULT_ABSOLUTE_ACCURACY = 1e-6;<a name="line.42"></a>
<FONT color="green">043</FONT>        /** Serializable version identifier */<a name="line.43"></a>
<FONT color="green">044</FONT>        private static final long serialVersionUID = -38038050983108802L;<a name="line.44"></a>
<FONT color="green">045</FONT>         /**<a name="line.45"></a>
<FONT color="green">046</FONT>          * RandomData instance used to generate samples from the distribution.<a name="line.46"></a>
<FONT color="green">047</FONT>          * @deprecated As of 3.1, to be removed in 4.0. Please use the<a name="line.47"></a>
<FONT color="green">048</FONT>          * {@link #random} instance variable instead.<a name="line.48"></a>
<FONT color="green">049</FONT>          */<a name="line.49"></a>
<FONT color="green">050</FONT>        @Deprecated<a name="line.50"></a>
<FONT color="green">051</FONT>        protected RandomDataImpl randomData = new RandomDataImpl();<a name="line.51"></a>
<FONT color="green">052</FONT>    <a name="line.52"></a>
<FONT color="green">053</FONT>        /**<a name="line.53"></a>
<FONT color="green">054</FONT>         * RNG instance used to generate samples from the distribution.<a name="line.54"></a>
<FONT color="green">055</FONT>         * @since 3.1<a name="line.55"></a>
<FONT color="green">056</FONT>         */<a name="line.56"></a>
<FONT color="green">057</FONT>        protected final RandomGenerator random;<a name="line.57"></a>
<FONT color="green">058</FONT>    <a name="line.58"></a>
<FONT color="green">059</FONT>        /** Solver absolute accuracy for inverse cumulative computation */<a name="line.59"></a>
<FONT color="green">060</FONT>        private double solverAbsoluteAccuracy = SOLVER_DEFAULT_ABSOLUTE_ACCURACY;<a name="line.60"></a>
<FONT color="green">061</FONT>    <a name="line.61"></a>
<FONT color="green">062</FONT>        /**<a name="line.62"></a>
<FONT color="green">063</FONT>         * @deprecated As of 3.1, to be removed in 4.0. Please use<a name="line.63"></a>
<FONT color="green">064</FONT>         * {@link #AbstractRealDistribution(RandomGenerator)} instead.<a name="line.64"></a>
<FONT color="green">065</FONT>         */<a name="line.65"></a>
<FONT color="green">066</FONT>        @Deprecated<a name="line.66"></a>
<FONT color="green">067</FONT>        protected AbstractRealDistribution() {<a name="line.67"></a>
<FONT color="green">068</FONT>            // Legacy users are only allowed to access the deprecated "randomData".<a name="line.68"></a>
<FONT color="green">069</FONT>            // New users are forbidden to use this constructor.<a name="line.69"></a>
<FONT color="green">070</FONT>            random = null;<a name="line.70"></a>
<FONT color="green">071</FONT>        }<a name="line.71"></a>
<FONT color="green">072</FONT>        /**<a name="line.72"></a>
<FONT color="green">073</FONT>         * @param rng Random number generator.<a name="line.73"></a>
<FONT color="green">074</FONT>         * @since 3.1<a name="line.74"></a>
<FONT color="green">075</FONT>         */<a name="line.75"></a>
<FONT color="green">076</FONT>        protected AbstractRealDistribution(RandomGenerator rng) {<a name="line.76"></a>
<FONT color="green">077</FONT>            random = rng;<a name="line.77"></a>
<FONT color="green">078</FONT>        }<a name="line.78"></a>
<FONT color="green">079</FONT>    <a name="line.79"></a>
<FONT color="green">080</FONT>        /**<a name="line.80"></a>
<FONT color="green">081</FONT>         * {@inheritDoc}<a name="line.81"></a>
<FONT color="green">082</FONT>         *<a name="line.82"></a>
<FONT color="green">083</FONT>         * The default implementation uses the identity<a name="line.83"></a>
<FONT color="green">084</FONT>         * &lt;p&gt;{@code P(x0 &lt; X &lt;= x1) = P(X &lt;= x1) - P(X &lt;= x0)}&lt;/p&gt;<a name="line.84"></a>
<FONT color="green">085</FONT>         *<a name="line.85"></a>
<FONT color="green">086</FONT>         * @deprecated As of 3.1 (to be removed in 4.0). Please use<a name="line.86"></a>
<FONT color="green">087</FONT>         * {@link #probability(double,double)} instead.<a name="line.87"></a>
<FONT color="green">088</FONT>         */<a name="line.88"></a>
<FONT color="green">089</FONT>        @Deprecated<a name="line.89"></a>
<FONT color="green">090</FONT>        public double cumulativeProbability(double x0, double x1) throws NumberIsTooLargeException {<a name="line.90"></a>
<FONT color="green">091</FONT>            return probability(x0, x1);<a name="line.91"></a>
<FONT color="green">092</FONT>        }<a name="line.92"></a>
<FONT color="green">093</FONT>    <a name="line.93"></a>
<FONT color="green">094</FONT>        /**<a name="line.94"></a>
<FONT color="green">095</FONT>         * For a random variable {@code X} whose values are distributed according<a name="line.95"></a>
<FONT color="green">096</FONT>         * to this distribution, this method returns {@code P(x0 &lt; X &lt;= x1)}.<a name="line.96"></a>
<FONT color="green">097</FONT>         *<a name="line.97"></a>
<FONT color="green">098</FONT>         * @param x0 Lower bound (excluded).<a name="line.98"></a>
<FONT color="green">099</FONT>         * @param x1 Upper bound (included).<a name="line.99"></a>
<FONT color="green">100</FONT>         * @return the probability that a random variable with this distribution<a name="line.100"></a>
<FONT color="green">101</FONT>         * takes a value between {@code x0} and {@code x1}, excluding the lower<a name="line.101"></a>
<FONT color="green">102</FONT>         * and including the upper endpoint.<a name="line.102"></a>
<FONT color="green">103</FONT>         * @throws NumberIsTooLargeException if {@code x0 &gt; x1}.<a name="line.103"></a>
<FONT color="green">104</FONT>         *<a name="line.104"></a>
<FONT color="green">105</FONT>         * The default implementation uses the identity<a name="line.105"></a>
<FONT color="green">106</FONT>         * {@code P(x0 &lt; X &lt;= x1) = P(X &lt;= x1) - P(X &lt;= x0)}<a name="line.106"></a>
<FONT color="green">107</FONT>         *<a name="line.107"></a>
<FONT color="green">108</FONT>         * @since 3.1<a name="line.108"></a>
<FONT color="green">109</FONT>         */<a name="line.109"></a>
<FONT color="green">110</FONT>        public double probability(double x0,<a name="line.110"></a>
<FONT color="green">111</FONT>                                  double x1) {<a name="line.111"></a>
<FONT color="green">112</FONT>            if (x0 &gt; x1) {<a name="line.112"></a>
<FONT color="green">113</FONT>                throw new NumberIsTooLargeException(LocalizedFormats.LOWER_ENDPOINT_ABOVE_UPPER_ENDPOINT,<a name="line.113"></a>
<FONT color="green">114</FONT>                                                    x0, x1, true);<a name="line.114"></a>
<FONT color="green">115</FONT>            }<a name="line.115"></a>
<FONT color="green">116</FONT>            return cumulativeProbability(x1) - cumulativeProbability(x0);<a name="line.116"></a>
<FONT color="green">117</FONT>        }<a name="line.117"></a>
<FONT color="green">118</FONT>    <a name="line.118"></a>
<FONT color="green">119</FONT>        /**<a name="line.119"></a>
<FONT color="green">120</FONT>         * {@inheritDoc}<a name="line.120"></a>
<FONT color="green">121</FONT>         *<a name="line.121"></a>
<FONT color="green">122</FONT>         * The default implementation returns<a name="line.122"></a>
<FONT color="green">123</FONT>         * &lt;ul&gt;<a name="line.123"></a>
<FONT color="green">124</FONT>         * &lt;li&gt;{@link #getSupportLowerBound()} for {@code p = 0},&lt;/li&gt;<a name="line.124"></a>
<FONT color="green">125</FONT>         * &lt;li&gt;{@link #getSupportUpperBound()} for {@code p = 1}.&lt;/li&gt;<a name="line.125"></a>
<FONT color="green">126</FONT>         * &lt;/ul&gt;<a name="line.126"></a>
<FONT color="green">127</FONT>         */<a name="line.127"></a>
<FONT color="green">128</FONT>        public double inverseCumulativeProbability(final double p) throws OutOfRangeException {<a name="line.128"></a>
<FONT color="green">129</FONT>            /*<a name="line.129"></a>
<FONT color="green">130</FONT>             * IMPLEMENTATION NOTES<a name="line.130"></a>
<FONT color="green">131</FONT>             * --------------------<a name="line.131"></a>
<FONT color="green">132</FONT>             * Where applicable, use is made of the one-sided Chebyshev inequality<a name="line.132"></a>
<FONT color="green">133</FONT>             * to bracket the root. This inequality states that<a name="line.133"></a>
<FONT color="green">134</FONT>             * P(X - mu &gt;= k * sig) &lt;= 1 / (1 + k^2),<a name="line.134"></a>
<FONT color="green">135</FONT>             * mu: mean, sig: standard deviation. Equivalently<a name="line.135"></a>
<FONT color="green">136</FONT>             * 1 - P(X &lt; mu + k * sig) &lt;= 1 / (1 + k^2),<a name="line.136"></a>
<FONT color="green">137</FONT>             * F(mu + k * sig) &gt;= k^2 / (1 + k^2).<a name="line.137"></a>
<FONT color="green">138</FONT>             *<a name="line.138"></a>
<FONT color="green">139</FONT>             * For k = sqrt(p / (1 - p)), we find<a name="line.139"></a>
<FONT color="green">140</FONT>             * F(mu + k * sig) &gt;= p,<a name="line.140"></a>
<FONT color="green">141</FONT>             * and (mu + k * sig) is an upper-bound for the root.<a name="line.141"></a>
<FONT color="green">142</FONT>             *<a name="line.142"></a>
<FONT color="green">143</FONT>             * Then, introducing Y = -X, mean(Y) = -mu, sd(Y) = sig, and<a name="line.143"></a>
<FONT color="green">144</FONT>             * P(Y &gt;= -mu + k * sig) &lt;= 1 / (1 + k^2),<a name="line.144"></a>
<FONT color="green">145</FONT>             * P(-X &gt;= -mu + k * sig) &lt;= 1 / (1 + k^2),<a name="line.145"></a>
<FONT color="green">146</FONT>             * P(X &lt;= mu - k * sig) &lt;= 1 / (1 + k^2),<a name="line.146"></a>
<FONT color="green">147</FONT>             * F(mu - k * sig) &lt;= 1 / (1 + k^2).<a name="line.147"></a>
<FONT color="green">148</FONT>             *<a name="line.148"></a>
<FONT color="green">149</FONT>             * For k = sqrt((1 - p) / p), we find<a name="line.149"></a>
<FONT color="green">150</FONT>             * F(mu - k * sig) &lt;= p,<a name="line.150"></a>
<FONT color="green">151</FONT>             * and (mu - k * sig) is a lower-bound for the root.<a name="line.151"></a>
<FONT color="green">152</FONT>             *<a name="line.152"></a>
<FONT color="green">153</FONT>             * In cases where the Chebyshev inequality does not apply, geometric<a name="line.153"></a>
<FONT color="green">154</FONT>             * progressions 1, 2, 4, ... and -1, -2, -4, ... are used to bracket<a name="line.154"></a>
<FONT color="green">155</FONT>             * the root.<a name="line.155"></a>
<FONT color="green">156</FONT>             */<a name="line.156"></a>
<FONT color="green">157</FONT>            if (p &lt; 0.0 || p &gt; 1.0) {<a name="line.157"></a>
<FONT color="green">158</FONT>                throw new OutOfRangeException(p, 0, 1);<a name="line.158"></a>
<FONT color="green">159</FONT>            }<a name="line.159"></a>
<FONT color="green">160</FONT>    <a name="line.160"></a>
<FONT color="green">161</FONT>            double lowerBound = getSupportLowerBound();<a name="line.161"></a>
<FONT color="green">162</FONT>            if (p == 0.0) {<a name="line.162"></a>
<FONT color="green">163</FONT>                return lowerBound;<a name="line.163"></a>
<FONT color="green">164</FONT>            }<a name="line.164"></a>
<FONT color="green">165</FONT>    <a name="line.165"></a>
<FONT color="green">166</FONT>            double upperBound = getSupportUpperBound();<a name="line.166"></a>
<FONT color="green">167</FONT>            if (p == 1.0) {<a name="line.167"></a>
<FONT color="green">168</FONT>                return upperBound;<a name="line.168"></a>
<FONT color="green">169</FONT>            }<a name="line.169"></a>
<FONT color="green">170</FONT>    <a name="line.170"></a>
<FONT color="green">171</FONT>            final double mu = getNumericalMean();<a name="line.171"></a>
<FONT color="green">172</FONT>            final double sig = FastMath.sqrt(getNumericalVariance());<a name="line.172"></a>
<FONT color="green">173</FONT>            final boolean chebyshevApplies;<a name="line.173"></a>
<FONT color="green">174</FONT>            chebyshevApplies = !(Double.isInfinite(mu) || Double.isNaN(mu) ||<a name="line.174"></a>
<FONT color="green">175</FONT>                                 Double.isInfinite(sig) || Double.isNaN(sig));<a name="line.175"></a>
<FONT color="green">176</FONT>    <a name="line.176"></a>
<FONT color="green">177</FONT>            if (lowerBound == Double.NEGATIVE_INFINITY) {<a name="line.177"></a>
<FONT color="green">178</FONT>                if (chebyshevApplies) {<a name="line.178"></a>
<FONT color="green">179</FONT>                    lowerBound = mu - sig * FastMath.sqrt((1. - p) / p);<a name="line.179"></a>
<FONT color="green">180</FONT>                } else {<a name="line.180"></a>
<FONT color="green">181</FONT>                    lowerBound = -1.0;<a name="line.181"></a>
<FONT color="green">182</FONT>                    while (cumulativeProbability(lowerBound) &gt;= p) {<a name="line.182"></a>
<FONT color="green">183</FONT>                        lowerBound *= 2.0;<a name="line.183"></a>
<FONT color="green">184</FONT>                    }<a name="line.184"></a>
<FONT color="green">185</FONT>                }<a name="line.185"></a>
<FONT color="green">186</FONT>            }<a name="line.186"></a>
<FONT color="green">187</FONT>    <a name="line.187"></a>
<FONT color="green">188</FONT>            if (upperBound == Double.POSITIVE_INFINITY) {<a name="line.188"></a>
<FONT color="green">189</FONT>                if (chebyshevApplies) {<a name="line.189"></a>
<FONT color="green">190</FONT>                    upperBound = mu + sig * FastMath.sqrt(p / (1. - p));<a name="line.190"></a>
<FONT color="green">191</FONT>                } else {<a name="line.191"></a>
<FONT color="green">192</FONT>                    upperBound = 1.0;<a name="line.192"></a>
<FONT color="green">193</FONT>                    while (cumulativeProbability(upperBound) &lt; p) {<a name="line.193"></a>
<FONT color="green">194</FONT>                        upperBound *= 2.0;<a name="line.194"></a>
<FONT color="green">195</FONT>                    }<a name="line.195"></a>
<FONT color="green">196</FONT>                }<a name="line.196"></a>
<FONT color="green">197</FONT>            }<a name="line.197"></a>
<FONT color="green">198</FONT>    <a name="line.198"></a>
<FONT color="green">199</FONT>            final UnivariateFunction toSolve = new UnivariateFunction() {<a name="line.199"></a>
<FONT color="green">200</FONT>    <a name="line.200"></a>
<FONT color="green">201</FONT>                public double value(final double x) {<a name="line.201"></a>
<FONT color="green">202</FONT>                    return cumulativeProbability(x) - p;<a name="line.202"></a>
<FONT color="green">203</FONT>                }<a name="line.203"></a>
<FONT color="green">204</FONT>            };<a name="line.204"></a>
<FONT color="green">205</FONT>    <a name="line.205"></a>
<FONT color="green">206</FONT>            double x = UnivariateSolverUtils.solve(toSolve,<a name="line.206"></a>
<FONT color="green">207</FONT>                                                       lowerBound,<a name="line.207"></a>
<FONT color="green">208</FONT>                                                       upperBound,<a name="line.208"></a>
<FONT color="green">209</FONT>                                                       getSolverAbsoluteAccuracy());<a name="line.209"></a>
<FONT color="green">210</FONT>    <a name="line.210"></a>
<FONT color="green">211</FONT>            if (!isSupportConnected()) {<a name="line.211"></a>
<FONT color="green">212</FONT>                /* Test for plateau. */<a name="line.212"></a>
<FONT color="green">213</FONT>                final double dx = getSolverAbsoluteAccuracy();<a name="line.213"></a>
<FONT color="green">214</FONT>                if (x - dx &gt;= getSupportLowerBound()) {<a name="line.214"></a>
<FONT color="green">215</FONT>                    double px = cumulativeProbability(x);<a name="line.215"></a>
<FONT color="green">216</FONT>                    if (cumulativeProbability(x - dx) == px) {<a name="line.216"></a>
<FONT color="green">217</FONT>                        upperBound = x;<a name="line.217"></a>
<FONT color="green">218</FONT>                        while (upperBound - lowerBound &gt; dx) {<a name="line.218"></a>
<FONT color="green">219</FONT>                            final double midPoint = 0.5 * (lowerBound + upperBound);<a name="line.219"></a>
<FONT color="green">220</FONT>                            if (cumulativeProbability(midPoint) &lt; px) {<a name="line.220"></a>
<FONT color="green">221</FONT>                                lowerBound = midPoint;<a name="line.221"></a>
<FONT color="green">222</FONT>                            } else {<a name="line.222"></a>
<FONT color="green">223</FONT>                                upperBound = midPoint;<a name="line.223"></a>
<FONT color="green">224</FONT>                            }<a name="line.224"></a>
<FONT color="green">225</FONT>                        }<a name="line.225"></a>
<FONT color="green">226</FONT>                        return upperBound;<a name="line.226"></a>
<FONT color="green">227</FONT>                    }<a name="line.227"></a>
<FONT color="green">228</FONT>                }<a name="line.228"></a>
<FONT color="green">229</FONT>            }<a name="line.229"></a>
<FONT color="green">230</FONT>            return x;<a name="line.230"></a>
<FONT color="green">231</FONT>        }<a name="line.231"></a>
<FONT color="green">232</FONT>    <a name="line.232"></a>
<FONT color="green">233</FONT>        /**<a name="line.233"></a>
<FONT color="green">234</FONT>         * Returns the solver absolute accuracy for inverse cumulative computation.<a name="line.234"></a>
<FONT color="green">235</FONT>         * You can override this method in order to use a Brent solver with an<a name="line.235"></a>
<FONT color="green">236</FONT>         * absolute accuracy different from the default.<a name="line.236"></a>
<FONT color="green">237</FONT>         *<a name="line.237"></a>
<FONT color="green">238</FONT>         * @return the maximum absolute error in inverse cumulative probability estimates<a name="line.238"></a>
<FONT color="green">239</FONT>         */<a name="line.239"></a>
<FONT color="green">240</FONT>        protected double getSolverAbsoluteAccuracy() {<a name="line.240"></a>
<FONT color="green">241</FONT>            return solverAbsoluteAccuracy;<a name="line.241"></a>
<FONT color="green">242</FONT>        }<a name="line.242"></a>
<FONT color="green">243</FONT>    <a name="line.243"></a>
<FONT color="green">244</FONT>        /** {@inheritDoc} */<a name="line.244"></a>
<FONT color="green">245</FONT>        public void reseedRandomGenerator(long seed) {<a name="line.245"></a>
<FONT color="green">246</FONT>            random.setSeed(seed);<a name="line.246"></a>
<FONT color="green">247</FONT>            randomData.reSeed(seed);<a name="line.247"></a>
<FONT color="green">248</FONT>        }<a name="line.248"></a>
<FONT color="green">249</FONT>    <a name="line.249"></a>
<FONT color="green">250</FONT>        /**<a name="line.250"></a>
<FONT color="green">251</FONT>         * {@inheritDoc}<a name="line.251"></a>
<FONT color="green">252</FONT>         *<a name="line.252"></a>
<FONT color="green">253</FONT>         * The default implementation uses the<a name="line.253"></a>
<FONT color="green">254</FONT>         * &lt;a href="http://en.wikipedia.org/wiki/Inverse_transform_sampling"&gt;<a name="line.254"></a>
<FONT color="green">255</FONT>         * inversion method.<a name="line.255"></a>
<FONT color="green">256</FONT>         * &lt;/a&gt;<a name="line.256"></a>
<FONT color="green">257</FONT>         */<a name="line.257"></a>
<FONT color="green">258</FONT>        public double sample() {<a name="line.258"></a>
<FONT color="green">259</FONT>            return inverseCumulativeProbability(random.nextDouble());<a name="line.259"></a>
<FONT color="green">260</FONT>        }<a name="line.260"></a>
<FONT color="green">261</FONT>    <a name="line.261"></a>
<FONT color="green">262</FONT>        /**<a name="line.262"></a>
<FONT color="green">263</FONT>         * {@inheritDoc}<a name="line.263"></a>
<FONT color="green">264</FONT>         *<a name="line.264"></a>
<FONT color="green">265</FONT>         * The default implementation generates the sample by calling<a name="line.265"></a>
<FONT color="green">266</FONT>         * {@link #sample()} in a loop.<a name="line.266"></a>
<FONT color="green">267</FONT>         */<a name="line.267"></a>
<FONT color="green">268</FONT>        public double[] sample(int sampleSize) {<a name="line.268"></a>
<FONT color="green">269</FONT>            if (sampleSize &lt;= 0) {<a name="line.269"></a>
<FONT color="green">270</FONT>                throw new NotStrictlyPositiveException(LocalizedFormats.NUMBER_OF_SAMPLES,<a name="line.270"></a>
<FONT color="green">271</FONT>                        sampleSize);<a name="line.271"></a>
<FONT color="green">272</FONT>            }<a name="line.272"></a>
<FONT color="green">273</FONT>            double[] out = new double[sampleSize];<a name="line.273"></a>
<FONT color="green">274</FONT>            for (int i = 0; i &lt; sampleSize; i++) {<a name="line.274"></a>
<FONT color="green">275</FONT>                out[i] = sample();<a name="line.275"></a>
<FONT color="green">276</FONT>            }<a name="line.276"></a>
<FONT color="green">277</FONT>            return out;<a name="line.277"></a>
<FONT color="green">278</FONT>        }<a name="line.278"></a>
<FONT color="green">279</FONT>    <a name="line.279"></a>
<FONT color="green">280</FONT>        /**<a name="line.280"></a>
<FONT color="green">281</FONT>         * {@inheritDoc}<a name="line.281"></a>
<FONT color="green">282</FONT>         *<a name="line.282"></a>
<FONT color="green">283</FONT>         * @return zero.<a name="line.283"></a>
<FONT color="green">284</FONT>         * @since 3.1<a name="line.284"></a>
<FONT color="green">285</FONT>         */<a name="line.285"></a>
<FONT color="green">286</FONT>        public double probability(double x) {<a name="line.286"></a>
<FONT color="green">287</FONT>            return 0d;<a name="line.287"></a>
<FONT color="green">288</FONT>        }<a name="line.288"></a>
<FONT color="green">289</FONT>    }<a name="line.289"></a>
<FONT color="green">290</FONT>    <a name="line.290"></a>




























































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